Linear perturbation analysis will be used to develop techniques for the interpretation of the results of computer simulation of systems involving many chemical reactions, especially (but not limited to) biological systems. The research will produce a computer program that will compute partial derivatives which summarize the sensitivity to enzymatic fluxes or system net flux to perturbations in enzyme or substrate concentrations. A similar sensitivity analysis will describe the tendency of a system in a given kinetic state to alter the concentrations of its constitutent chemicals. Stability analysis will be used to predict the direction through concentration space in which a system will tend to move at any instant. The above calculations will yield insights into the control of a multireaction pathway by its chemical constituents (especially enzymes for biological systems). This will have great singificance for understanding the complexities of metabolic regulation. Inverse sensitivity analysis will be used to determine the maximum tolerable errors in the values of a system's parameters so that the maximum likely error in a computer model's predictions will be within the error in the experimental data on which the model is based. If the maximum parameter errors are relatively large, the model is not overly sensitive to the values of its parameters, thus increasing confidence in the reliability of its predictions.